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This note explores the applicability of unsupervised machine learning techniques towards hard optimization problems on random inputs.
Computers and intractability: A guide to the theory of NP-completeness
M. R. Garey and D. S. Johnson · 1990
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C. Watkins and P. Dayan · 1992
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Punctuated equilibrium and criticality in a simple model of evolution
P. Bak and K. Sneppen · 1993
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Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programing
M. X. Goemans and D. P. Williamson · 1995
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Extremal optimization: Methods derived from co-evolution
S. Boettcher and A. G. Percus · 1999
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Policy gradient methods for reinforcement learning with function approximation
R. S. Sutton, D. A. McAllester, S. P. Singh, and Y. Mansour · 1999
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Nature’s way of optimizing
S. Boettcher and A. G. Percus · 2000
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Extremal optimization for graph partitioning
S. Boettcher and A. G. Percus · 2001
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A new model for learning in graph domains
M. Gori, G. Monfardini, and F. Scarselli · 2005
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The parisi formula
Michel Talagrand · 2006
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Optimization with extremal dynamics for the traveling salesman problem
Yu-Wang Chen, Yong-Zai Lu, and Peng Chen · 2007
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The peculiar phase structure of random graph bisection
Allon G Percus, Gabriel Istrate, Bruno Gonçalves, Robert Z Sumi, and Stefan Boettcher · 2008
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F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
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Lenka Zdeborová and Stefan Boettcher · 2010
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Model-free reinforcement learning with continuous action in practice
T. Degris, P. M. Pilarski, and R. S. Sutton · 2012
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Florent Krzakala, Cristopher Moore, Elchanan Mossel, Joe Neeman, Allan Sly, Lenka Zdeborová, and Pan Zhang · 2013
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Alaa Saade, Florent Krzakala, and Lenka Zdeborová · 2014
Learning multiagent communication with backpropagation
S. Sukhbaatar, A. Szlam, and R. Fergus · 2016
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Semidefinite programs on sparse random graphs and their application to community detection
Andrea Montanari and Subhabrata Sen · 2016
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Community detection and stochastic block models: recent developments
Emmanuel Abbe · 2017
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Extremal cuts of sparse random graphs
A. Dembo, A. Montanari, and S. Sen · 2017
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Geometric deep learning: Going beyond euclidean data
M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, and P. Vandergheynst · 2017
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Supervised community detection with line graph neural networks
Z. Chen, X. Li, and J. Bruna · 2017
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Non-backtracking spectrum of random graphs: community detection and non-regular ramanujan graphs
Charles Bordenave, Marc Lelarge, and Laurent Massoulié · 2015
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Gated graph sequence neural networks
Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel · 2015
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Convolutional networks on graphs for learning molecular fingerprints
D. Duvenaud, D. Maclaurin, J. Aguilera-Iparraguirre, A. Aspuru-Guzik R. Gómez-Bombarelli, T. Hirzel, and R. P. Adams · 2015
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SDPNAL+: a majorized semismooth newton-cg augmented lagrangian method for semidefinite programming with nonnegative constraints
Liuqin Yang, Defeng Sun, and Kim-Chuan Toh · 2015
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Notes on computational-to-statistical gaps: predictions using statistical physics
Afonso S Bandeira, Amelia Perry, and Alexander S Wein · 2018
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Optimization of the Sherrington-Kirkpatrick hamiltonian
Andrea Montanari · 2018
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Revised note on learning quadratic assignment with graph neural networks
Alex Nowak, Soledad Villar, Afonso S Bandeira, and Joan Bruna · 2018
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Implementation of GNN, SDP and EO for max-cut
Weichi Yao · 2019
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